• Shailesh Nalavadi
• Mrs. Ashwini D S
• Shivaprasad R B
• Shubhadeep Moitra
• Y S V S Tarun Kaashyap

This paper of introduction represents a type of arthritis known as knee osteoarthritis is characterized by stiffness, joint space, osteophytic growth, and bone deformity which can be seen on radiographs. This is a disease caused by cartilage degeneration in the knee. Cartilage acts as a layer at the end of the bone, allowing the joint to move. When cartilage breaks down, it causes knee pain, stiffness, swelling and reduced mobility. As you get older, your risk of developing osteoarthritis increases due to wear and tear on your joints. We collect data from knee X-ray or MRI images and collect representative and diverse data to ensure that the information is a mix of healthy patients and osteoarthritis pain. We use deep learning architecture to classify images. We use convolutional neural networks for this purpose. We use the training process to train the model and then use the validation process to check its performance. We utilize measurements such as exactness, precision, review, and F1 score to assess the execution of the model. To understand negative and negative, we create a confusion matrix. We constantly update information to improve performance standards.

Knee Osteoarthritis, Medical Imaging, Computer-aided Diagnosis, Convolutional Neural Networks.

"Detection and Deployment of Knee Osteoarthritis using Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.h706-h712, May-2024, Available :http://www.jetir.org/papers/JETIR2405790.pdf

"Detection and Deployment of Knee Osteoarthritis using Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. pph706-h712, May-2024, Available at : http://www.jetir.org/papers/JETIR2405790.pdf